Building a high-performing AI solution requires plenty of development time, but also lots of testing. While some part of this process can be carried out by QA engineers, in the case of language processing models, the output needs to be checked and evaluated by professional human linguists. Whether it’s spoken or written language, our team helps provide structured feedback to optimise your algorithm so that it sounds and feels as human as possible.
Human language is unique among all forms of communication. Every conversation or written text has a myriad of subtle details and intricacies that convey meaning beyond the surface level. While it has been demonstrated that some AI models are smart enough to understand jokes, there are certain aspects of culture and humour that still remain intrinsically human.
Did you know that AI still can’t make full sense of memes? While it can recognise text and facial expressions, memes relying so heavily on our own life experience, cultural references, subtext and shared knowledge make it a challenging task for AI.
Perhaps the most important thing is that human language isn’t a fixed thing. On the contrary, it is an ever-evolving phenomenon as it changes and adapts over time, reflecting the evolution of societies, cultures, and communication patterns.
As new linguistic patterns, vocabulary and expressions emerge, AI models trained on older data become less effective. Retraining AI models with updated and relevant data helps them adapt to these changes and maintain their performance over time.
More and more companies are leveraging artificial intelligence, especially when it comes to content production. Using tools like ChatGPT allows teams to produce high-quality content while saving time and resources. However, whether it is blog posts, social media captions, email newsletters, product descriptions or images that you generate with this type of tool, they still require human checking and editing to ensure accuracy, brand consistency, and adherence to ethical guidelines.
We validate the usage of industry-specific terminology, cross-referencing content with authoritative sources, or utilising glossaries and style guides specific to your organisation.
Let’s talk about your next project